COMPUTER SCIENCE COLLOQUIUM

Measures of Semantic Relatedness and the Detection and Correction
of Real-Word Spelling Errors

Graeme Hirst
University of Toronto

Monday, April 8, 2002
3:00 p.m.
Heller Hall 302

Abstract

Lexical semantic relatedness in text reflects cohesion in the text. 
Lexical semantic relationships include synonymy, hypernymy, and meronymy.  
But what degree of closeness by such links counts as semantic relatedness  
and how it can be measured?  We experimentally compared five different  
proposed measures of similarity or semantic relatedness in WordNet by  
examining their performance in a real-word spelling correction system.  We  
will discuss what these results mean for applications in NLP, and also 
outline a method of real-word spelling correction that approaches 
practical usefulness. 

Bio

Graeme Hirst's research has covered a broad but integrated range of topics  
in computational linguistics, natural language understanding, and related  
areas of cognitive science. These include the resolution of ambiguity in  
language understanding; psychological reality in natural language systems;  
the preservation of author's style in machine translation; recovering from  
misunderstanding and non-understanding in human-computer communication;  
and linguistic constraints on knowledge- representation systems. His  
present research includes the problem of near-synonymy in lexical choice  
in language generation; computer assistance for collaborative writing; and  
applications of lexical chaining as an indicator of semantic distance in  
texts.